All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale^1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter⁴; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation^5,6; analyses timings and patterns of tumour evolution⁷; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity^8,9; and evaluates a range of more-specialized features of cancer genomes^8,10–18.

We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

Introduction: The human genome is peppered with mobile repetitive elements called long interspersed nuclear element–1 (L1) retrotransposons. Propagating through RNA and cDNA intermediates, these molecular parasites copy and insert themselves throughout the genome, with potentially disruptive effects on neighboring genes or regulatory sequences. In the germ line, unique sequence downstream of L1 elements can also be retrotransposed if transcription continues beyond the repeat, a process known as 3′ transduction. There has been growing interest in retrotransposition and 3′ transduction as a possible source of somatic mutations during tumorigenesis. Rationale: To explore whether 3′ transductions are frequent in cancer, we developed a bioinformatic algorithm for identifying somatically acquired retrotranspositions in cancer genomes. We applied our algorithm to 290 cancer samples from 244 patients across 12 tumor types. The unique downstream sequence mobilized with 3′ transductions effectively fingerprints the L1 source element, providing insights into the activity of individual L1 loci across the genome. Results: Across the 290 samples, we identified 2756 somatic L1 retrotranspositions. Tumors from 53% of patients had at least one such event, with colorectal and lung cancers being most frequently affected (93% and 75% of patients, respectively). Somatic 3′ transductions comprised 24% of events, half of which represented mobilizations of unique sequence alone, without any accompanying L1 sequence. Overall, 95% of 3′ transductions identified derived from only 72 germline L1 source elements, with as few as four loci accounting for 50% of events. In a given sample, the same source element could generate 50 or more somatic transductions, scattered extensively across the genome. About 5% of somatic transductions arose from L1 source elements that were themselves somatic retrotranspositions. In three of the cases in which we sequenced more than one sample from a patient’s tumor, we were able to place 3′ transductions on the phylogenetic tree. We found that the activity of individual source elements fluctuated during tumor evolution, with different subclones exhibiting much variability in which elements were “on” and which were “off.” The ability to identify the individual L1 source elements active in a given tumor enabled us to study the promoter methylation of those elements specifically. We found that 3′ transduction activity in a patient’s tumor was always associated with hypomethylation of that element. Overall, 2.3% of transductions distributed exons or entire genes to other sites in the genome, and many more mobilized deoxyribonuclease I (DNAse-I) hypersensitive sites or transcription factor binding sites identified by the ENCODE project. Occasionally, somatic L1 insertions inserted near coding sequence and redistributed these exons elsewhere in the genome. However, we found no general effects of retrotranspositions on transcription levels of genes at the insertion points and no evidence for aberrant RNA species resulting from somatically acquired transposable elements. Indeed, as with germline retrotranspositions, somatic insertions exhibited a strong enrichment in heterochromatic, gene-poor regions of the genome. Conclusion: Somatic 3′ transduction occurs frequently in human tumors, and in some cases transduction events can scatter exons, genes, and regulatory elements widely across the genome. Dissemination of these sequences appears to be due to a small number of highly active L1 elements, whose activity can wax and wane during tumor evolution. The majority of the retrotransposition events are likely to be harmless “passenger” mutations.